Data Denoising and Compression for Smart Grid Communication

Khan, Jesmin; Bhuiyan, Sharif; Murphy, Gregory; Williams, Johnathan

doi:10.1109/tsipn.2016.2539680

Cited by 37 publications

(27 citation statements)

References 30 publications

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“…Thus, a few bad data points do not affect the overall trend of system energy, which is used to locate the oscillation source. But the data preprocessing, as presented in [18] can be performed for better performance by reducing the measurement noise or distortion.…”

Section: A Accurate Oscillation Location Methods For Dfig-wtmentioning

confidence: 99%

An Accurate Forced Oscillation Location and Participation Assessment Method for DFIG Wind Turbine

et al. 2019

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With the integration of wind energy, the widely used doubly fed induction generator wind turbines (DFIG-WT) could induce Power System forced oscillations (FOs), which threaten the safety of power grid. In this paper, an accurate FOs location method is proposed to pinpoint sources of FOs to the specific components inside a DFIG-WT and a participation assessment method is proposed to evaluate the role of DFIG-WTs in the FOs event. Firstly, the energy structure of the DFIG-WT is constructed and the correspondence between the physical components and energy structure of the DFIG-WT is established. Thus, the sources of FOs can be located by the energy flow among the converter, wind turbine and induction generator. Furthermore, the port-controlled Hamiltonian (PCH) method is used to analyze the influence of external disturbances to the potential energy of DFIG-WT, based on which the participation factor of the DFIG-WT in FOs event can be defined. The simulation results demonstrate that the proposed method is able to locate the oscillation sources accurately and reveal the participation of the DFIG-WT in FOs events effectively.

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Section: A Accurate Oscillation Location Methods For Dfig-wtmentioning

confidence: 99%

An Accurate Forced Oscillation Location and Participation Assessment Method for DFIG Wind Turbine

et al. 2019

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“…There are several works on compressing data and signal associated with the power system using lossless compression algorithms [10][11][12][13]. In the smart grid, the management of load profile data produced by smart meters is extremely challenging and some works are available for compressing these data [3,4].…”

Section: Related Workmentioning

confidence: 99%

Development of lossless compression algorithms for power system operational data

Sarkar

Kundu

Sarkar

2018

IET Generation, Transmission & Distribution

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“…The fixed wavelet and scale may not be suitable for other signals. In [19,20], a wavelet packet decomposition (WPD)-based data compression method, which is an expansion of wavelet decomposition (WD), was proposed for better accuracy. The best wavelet and scale were selected based on the maximum wavelet energy as well.…”

Section: Introductionmentioning

confidence: 99%

“…However, there are two main problems in the above WT-based methods: 1) it is difficult to select the optimal wavelet functions and decomposition scales with a balanced compression performance and reconstruction accuracy; 2) most of the above methods are only suitable for the compression of disturbance signals. For example, the MDL method is used for extracting abrupt changes from disturbance signals [24], and the criterion of maximum wavelet energy [18][19][20] means retaining the information of abrupt changes as much as possible. These approaches are not suitable for oscillations, such as LFOs and SSOs.…”

Section: Introductionmentioning

confidence: 99%

Wavelet-based data compression for wide-area measurement data of oscillations

Cheng

Zhang

et al. 2018

J. Mod. Power Syst. Clean Energy

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This paper proposes a wavelet-based data compression method to compress the recorded data of oscillations in power systems for wide-area measurement systems. Actual recorded oscillations and simulated oscillations are compressed and reconstructed by the waveletbased data compression method to select the best wavelet functions and decomposition scales according to the criterion of the minimum compression distortion composite index, for a balanced consideration of compression performance and reconstruction accuracy. Based on the selections, the relationship between the oscillation frequency and the corresponding optimal wavelet and scale is discussed, and a piecewise linear model of the base-2 logarithm of the frequency and the order of the wavelet is developed, in which different pieces represent different scales. As a result, the wavelet function and decomposition scale can be selected according to the oscillation frequency. Compared with the wavelet-based data compression method with a fixed wavelet scale for disturbance signals and the real-time data compression method based on exception compression and swing door trending for oscillations, the proposed method can provide high compression ratios and low distortion rates.

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Data Denoising and Compression for Smart Grid Communication

Cited by 37 publications

References 30 publications

An Accurate Forced Oscillation Location and Participation Assessment Method for DFIG Wind Turbine

An Accurate Forced Oscillation Location and Participation Assessment Method for DFIG Wind Turbine

Development of lossless compression algorithms for power system operational data

Wavelet-based data compression for wide-area measurement data of oscillations

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